压缩机附属管线振动状态的监测与预测研究

发布时间：2018-04-11 16:41

本文选题：压缩机附属管线振动 + 状态监测　；参考：《华东理工大学》2017年硕士论文

【摘要】：在化工企业长期存在着“重设备轻管道”的思想,压缩机组作为化工装置的核心设备,与其相关的状态监测与故障诊断的研究较多。管道振动也是石化企业的安全隐患之一,然而对于压缩机附属管线的振动状态监测的研究却非常少,在企业中,管道振动状态的评估仍然停留在感官判断上。综上所述,本文就压缩机附属管线的振动进行深入研究。首先,介绍了压缩机及其附属管线基础的振动理论,包括压缩机分类和三类压缩机工作原理,以及往复式与螺杆式压缩机的附属管线的振动机理。其次,比较了API标准、ASME标准与ISO标准三种压缩机附属管线振动状态评估方法,并选取API系列标准作为振动状态的评价依据。结合石化公司项目实例,得到了需要重点监测以及需要整改的管线。由于灰色-马尔可夫链模型适用于小样本数据的短期预测,而本研究需要根据少量点检数据预测管道振动状态,因此采用灰色-马尔可夫链模型预测管道未来的振动状态。灰色-马尔可夫链模型以灰色GM(1,1)模型预测短期的管线振动数据,并根据预测数列以马尔可夫链模型预测未来管线振动的最大概率状态。最后,采用Labview开发了管道振动数据的时域分析、频域分析和趋势图分析功能,初步形成了用于管道振动状态监测和性能预测的软件。
[Abstract]:The idea of "heavy equipment and light pipeline" exists in chemical enterprises for a long time. As the core equipment of chemical plant, the research on condition monitoring and fault diagnosis related to compressor unit is much more.Pipeline vibration is also one of the hidden safety problems in petrochemical enterprises. However, there is little research on monitoring the vibration state of the pipeline attached to the compressor. In the enterprise, the evaluation of pipeline vibration status is still focused on sensory judgment.To sum up, the vibration of the pipeline attached to the compressor is studied in this paper.Firstly, the vibration theory of compressor and its subsidiary pipeline foundation is introduced, including the classification of compressor and the working principle of three kinds of compressors, as well as the vibration mechanism of auxiliary pipelines of reciprocating and screw compressors.Secondly, three methods for evaluating the vibration state of the pipeline attached to the compressor are compared between the API standard and the ISO standard, and the API series standards are selected as the basis for the evaluation of the vibration state.Combined with the project example of petrochemical company, the pipeline needs to be monitored and rectified.The grey-Markov chain model is suitable for the short-term prediction of small sample data, but this study needs to predict the pipeline vibration state based on a small amount of spot check data, so the grey-Markov chain model is used to predict the future vibration state of the pipeline.Gray Markov chain model is used to predict short-term pipeline vibration data and Markov chain model is used to predict the maximum probability state of pipeline vibration in the future.Finally, the functions of time-domain analysis, frequency-domain analysis and trend chart analysis of pipeline vibration data are developed by using Labview, and a software for pipeline vibration state monitoring and performance prediction is preliminarily formed.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TQ051.21

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